This disclosure relates generally to a computer software system and associated method for storage and retrieval of data in XML documents, and more particularly to a data structure for encoding XML data with tokens and identifier sequences.
Extensible Markup Language (XML) is a programming language operating as an extension to HTML and providing enhanced control of content. It may be used to define the content of a document (such as a Web page) rather than the presentation of it or to exchange information and documents between diverse systems. XML is text-based and formats data by using document tags to catalog information. Key elements in a document may be categorized according to meaning, enabling a search engine to scan an entire document for the XML tags that identify individual pieces of text and images rather than selecting a document by the metatags listed in its header.
There are various strategies for storing and managing XML documents. In XML repositories based on relational database technology, the XML is stored using a method known as “shredding”. In this approach, the markup is broken up and stored in fields of database tables, and XML queries are translated into a relational query language (e.g. SQL, Structured Query Language) that retrieves the values from the database using relational operations, and generates the markup output. Overhead for storage is high, and performance for regeneration of the XML (or “round-tripping” of entire XML documents) is typically low. Other database managers designed specifically for XML utilize indexing schemes to process the markup representation of XML more efficiently.
An example of one approach to querying XML documents is presented in U.S. Pat. No. 6,654,734 to Mani et al. (“System and Method for Query Processing and Optimization for XML Repositories”). The query system of Mani et al. views the data in XML documents as a graph that allows queries on content, structure, inter-document links, and intra-document links. The query language is based on tree pattern match semantics using XML semantics, with features that allow the query system to compute a document type definition for the query language and use it to validate the user query formulation. Query optimization is accomplished using schema-based optimization and index-based optimization. The structure pattern is then converted to a string for storage purposes.
Another approach is described in U.S. patent application Publication No. 2002/0169788 to Lee et al. (“System and Method for Automatic Loading of an XML Document Defined by a Document-Type Definition into a Relational Database Including the Generation of a Relational Schema Therefor”). Under the system of Lee et al., a relational schema is created out of a DTD, and SML data is loaded into the generated relational schema that adheres to the DTD. Starting with a DTD for an XML document containing data, all of the information in the DTD is captured into metadata tables, and then the metadata tables are queried to generate the relational schema. The data contained in the XML document can then be loaded into the generated relational schema.
However, utilizing relational database management technology for the storage and retrieval of data in large XML document can be inefficient both in time and space. These systems require both an RDBMS and a front-end for inserting and regenerating the XML. It would be desirable to have an XML database manager that can be deployed on user's machines, as well as centralized servers, that would have a small footprint for the executables and a space-efficient storage strategy, as well as a high-performance implementation of a general-purpose XML query language, such as XQuery.